Clostridium difficile infection (CDI) is a global public health problem with increases in incidence and severity of disease being reported from several countries [1–4]. In the United States, an estimated 14 000 deaths associated with CDI occurred in 2007 based on death certificate data, with an estimated excess in medical costs related to CDI of up to $4.8 billion in US acute care facilities [5, 6]. Clostridium difficile infection is now recognized to occur outside acute care hospitals, and reports of CDI among individuals in the community or in nursing homes have become increasingly common in the last few years [7–10]. Some of these patients do not require hospitalization for CDI treatment and are treated in outpatient or in nonacute care settings where the diagnosis of CDI was made [10, 11]. Therefore, population-level data are important for understanding the total burden of CDI at the national level.

Accurate estimates of CDI nationally will require accounting for factors that influence CDI rates. Several factors such as age, sex, or type of C difficile diagnostic assay may influence incidence measures. Incidence of CDI is known to be higher among the elderly population, especially those over 65 years of age [1, 12, 13]. In addition, females seem to be more affected than males in some studies focusing on community-associated (CA) CDI [14, 15]. Finally, at least 8 nucleic acid amplification tests (NAATs) have been approved by the US Food and Drug Administration since 2009 [16]. These assays have a higher sensitivity than the traditional C difficile toxin assays, and some studies have shown that use of NAAT can increase the rate of diagnosed CDI at least 2-fold [17–19].

Understanding the population- or diagnostic-specific factors that influence CDI incidence measures is important for meaningful comparisons of CDI rates across facilities, states, and regions and for accurate national burden estimates.

From January 1 through December 31, 2010, a total of 10 062 CDI cases among 9450 unique patients were identified; 8890 (94.1%) patients had a single incident episode, 512 (5.4%) patients had 2 incident episodes, 44 (0.5%) patients had 3 incident episodes, and 4 patients had 4 incident episodes during the calendar year. Of the 10 062 CDI cases identified, 2777 (27.6%) were estimated to be diagnosed by NAAT based on laboratory survey. Minnesota was the site with the highest percentage of cases (88.1%) detected by NAAT, followed by New York (41.9%), Colorado (29.5%), California (26.7%), Georgia (9.8%), and Connecticut (4.5%). Oregon was the only site with no cases identified by NAAT.

Of the 10 062 CDI cases, 32% were CA, 26% were NHO, 23% were HO, and 19% were CO-HCFA (Table 1). The proportion of CDI cases in each epidemiologic class varied greatly across sites. Minnesota and Oregon, the only 2 sites with rural counties, had the highest proportion of CA-CDI cases, 51% and 53%, respectively (Table 1). Table 1.

Clostridium difficile Infection (CDI) Cases by Surveillance Site and Epidemiologic Category, 2010

This analysis including data from 7 US states, encompassing a population of ∼10 million persons, showed that elderly patients, females, and those of white race seem to be at higher risk of CDI. Incidence of CDI has been reported to be higher among persons 65 years of age or older in several studies [1, 12, 13]. This result may be related to increased exposures to healthcare settings, increased antibiotic use, and impaired immune response to infectious pathogens [23–25]. Some studies have reported higher CDI incidence in females compared with males for CA infections; however, we observed that for both CA- and HA-CDI, females appear to be at higher risk [14, 15]. Although C difficile has been increasingly reported among peripartum women [26, 27], and females seem to be at increased risk of recurrent CDI [28], the reasons for the higher risk of CDI in females compared with males are still not clear. However, some possible explanations have been raised but not proven. Females may have greater exposure to infants who are known to have a high C difficile colonization rate, and infant exposure has been described as a risk factor for CA-CDI [8]. In addition, females are more likely to seek medical care, resulting in increased exposure to antibiotics [29]. A study in England and Wales showed that antibiotic prescribing rates in females were 40% higher compared with males [30]. Finally, host factors related to immune system may explain some of the differences in CDI rates between females and males [31].

Another interesting finding in our study was the ∼50% higher incidence among whites compared with blacks and 3-fold higher incidence of whites compared with other nonblack races. The relationship between white race and CDI has not been previously described. Many CDI published studies have either not collected race information or have not found a significant correlation between race and CDI. Although the reasons for white individuals to be at increased risk of CDI compared with other races are not known: one can hypothesize that greater access to healthcare and, therefore, the potential for more antibiotic exposure or increased diagnostic testing may play a role in the differences in race-specific CDI incidence we observed [32, 33].

According to our results, differences in CDI incidence across geographic locations can be partially explained by the type of diagnostic tests used for C difficile; demographic characteristics of the population such as age, sex, and race; and increased healthcare utilization. The remaining differences in adjusted CDI rates across states, especially for HA-CDI, suggest that other factors not accounted for in our analyses, such as differences in antibiotic prescribing practices, infection control practices, or the occurrence of C difficile outbreaks during the surveillance period, may also play a role in the variability of CDI incidence across states. Although some studies have shown an association of NAAT with increased CDI incidence [17–19], we did not find NAAT use to be significantly associated with population level differences in HA-CDI incidence across states. It is possible that in contrast to CA-CDI rates, HA-CDI rates may be driven more by patient age and other healthcare facility characteristics, such as volume of patients admitted and severity of illness of patients receiving care at the facilities, rather than the type of diagnostic test used. Nevertheless, our findings are critical to informing comparisons of CDI population-based rates across states and regions and to developing more robust national burden estimates of CDI that account for major determinants when projecting CDI rates to the national level. We plan to use these factors when we analyze EIP CDI surveillance data in the future to inform national rates.

Finally, the 32% of CA-CDI cases we found is higher than the rates of 20%–27% reported in Canada and in one region of the United States using a similar definition [14, 34]. This higher proportion of CA-CDI cases may be explained by the inclusion of large commercial and outpatient laboratories in the surveillance. Similar to a study done in the United Kingdom [8], we also found that the 2 EIP sites, Minnesota and Oregon, with a more rural population under surveillance had a higher prevalence of CA-CDI cases compared with other sites with a more urban population, which may be related to either healthcare utilization factors or different sources of C difficile exposures. In addition, the crude incidence of CA-CDI we observed across sites of 28–79/100 000 population is higher than the crude incidence of 20–40/100 000 population that has been reported in other population-based studies before the introduction of molecular diagnostic tests for C difficile [8, 35]. Despite this large proportion of CA-CDI cases, the majority of CDI cases (68%) are still HA with disease onset either in nursing homes, hospitals, or within 12 weeks after discharge from a healthcare facility. Moreover, as previously reported, the majority of CA-CDI cases are related to the receipt of outpatient care [11].

This study has several limitations. First, we were not able to capture antibiotic prescribing data in our surveillance sites. Antibiotics are known to be a major risk factor for CDI [36, 37], and variability in prescribing practices across regions has been documented [24]. Second, the data on NAAT utilization were captured through a survey of participating laboratories, and it is possible that some CDI cases may have been misclassified as being identified by NAAT, especially in laboratories using NAAT as a second-line test. Third, classification of CA-CDI cases was based on medical record documentation and, therefore, some cases may have been misclassified if no documentation of prior hospitalization was available. However, a previous study using the same surveillance population [11] showed that misclassification only occurred in ∼6% of CA-CDI cases. Finally, the incidence calculation relied on positive C difficile test, and it is possible that some patients may have been misclassified as cases if C difficile stool testing was not limited to patients with ≥3 unformed stools per 24 hour period as recommended by laboratory practice guidelines [38].

In conclusion, CA-CDI rates vary by age, sex, race, and type of diagnostic test, whereas HA-CDI rates vary by age and average number of inpatient-days per hospitals in a region. These factors must be taken into account for meaningful comparison of CDI incidence across different geographic locations and for more reliable projections of CDI burden in the United States.